A contact center, such as a call center, is a system that enables a staff of agents to service telephone calls to or from customers or other constituents. Modern contact centers generally incorporate computer-based systems for handling calls and managing databases. The contact center usually maintains, and from time-to-time updates, a database of the qualifications of each agent that are readily available and relevant to servicing calls. Specialized product skills and foreign language fluency typify the information held in an agent database.
The contact center's computer-based systems typically route each incoming call to an agent who is available and qualified to service the call. Coupled to these systems are queues for holding incoming calls that await service by an available agent. The contact center typically organizes its agents into “queue groups;” each queue group consists of agents with similar qualifications and services calls from a queue. A highly qualified agent, for example, might be a member of two or more queue groups.
The center's computer-based systems assess and categorize each incoming call, for example in terms of a caller's product interest and language preference. Based on the categorization, a software program matches the call to an appropriate queue for service by an agent in the corresponding queue group. The queue holds the call until an agent from the queue group receives and services it. In short, the contact center categorizes and holds each incoming call for service by an appropriately qualified agent.
Conventional contact centers typically approach call handling from a timing perspective. When a queue holds multiple calls, the conventional contact center generally serves next the call that has been waiting longest. In other words, in each specified category of call, the next call served is typically the longest call waiting. When multiple agents in a queue group are idle and the queue that holds calls is empty, the conventional contact center typically routes the next incoming call to the agent who has been idle the longest.
The call-distribution function, commonly referred to as automatic call distribution (“ACD”), is generally implemented in software that executes in a switching system, such as a private branch exchange, that connects customer calls to agent telephones. The ACD component typically includes a software module, known as a rules-based distribution engine (“RBDE”), which categorizes each incoming call and selects an appropriate holding queue based on the categorization. In response to the RBDE's queue selection, the ACD places each incoming call in an appropriate queue. The RBDE's rules select the next call to be served from the queue and match that call with an available agent from the corresponding queue group. The ACD then activates a physical switch in the switching system that routes the call to the matched agent.
In modem contact centers, personnel interact with the center's component systems through a centralized system known as a computer/telephone integration system (“CTI”). The CTI system cooperates with the ACD and an intelligent voice response system (“IVRS”) to acquire information about incoming calls. The IVRS queries each incoming caller regarding call purpose, product interest, and language requirements, for example. The ACD examines the call signal patterns to determine telephony aspects of a call such as the caller's location and telephone number. The IVRS deduces additional information about the call by referencing the information acquired by the ACD and the IVRS to the contact center's databases.
The conventional art includes various methods for selecting an agent to service an incoming call and thereby derive benefit for the center from the call-agent interaction. The conventional methods generally focus on a modified version of one of the conventional functions described above in this Background. The conventional art includes refined approaches to assessing incoming calls, to characterizing agent qualifications, and to matching the assessment of the call to the qualifications of the agents who are eligible to service the call. However, contact centers operate under dynamic situational and environmental factors and with agents whose individual performance and proficiencies change over time. In these conditions, the characteristics of the preferred agent to take a given call can vary significantly and the conventional methods exhibit shortcomings.
A contact center's call volume generally fluctuates, both predictably and unpredictably. When call volume is high, an agent with a history of handling calls quickly but with average quality may produce more value for the contact center than would an agent with a history of handling calls slowly but with high quality.
It is not uncommon for a contact center's management to alter the center's objectives. Management may gauge the center's operational effectiveness according to profit in one season and according to maximum number of customers served in a later season, for example. In the first season, an agent with a history of meticulously converting calls into high-dollar sales might make a larger contribution to the operational effectiveness of the contact center than would an agent with a history of rapidly converting calls into small-dollar sales. But for the later season, the fast-selling agent might make the larger contribution to the overall objective of the organization.
Agent qualifications generally change through training, experience, and management guidance. The change is sometimes rapid and unpredictable. For example, suppose an agent receives computer-based training during a 15-minute break to learn about a special promotional offer. The promotion just aired in an infomercial and inundated the center with inquiries. The center's operational effectiveness may be served by routing inquiries to the newly trained agent immediately following the 15-minute training break.
Agent qualifications are not always directly correlated to agent performance. For example, a highly qualified, highly trained agent might handle calls slowly. The slow-handling condition might be correlated to a situation or measurable parameter. For example, suppose an infomercial periodically airs a promotional offer that predictably triggers a backlog of impatient callers and a spike in call volume. Some agents, who are excellent performers on average, may buckle under the pressure. For these agents, performance may be linked to call volume.
Contact centers often monitor agent performance and describe that performance using several metrics. Typical metrics include handling time, quality, cross sales, first call resolution, and close ratio. Depending on the situation, each of these metrics may have a different relevance to the operational effectiveness of a contact center. In some situations, close ratio and, to a lesser degree, cross sales might both be relevant to operational effectiveness. For example, an infomercial might sell diamonds one hour and gold jewelry the next. During the diamond hour, when call volume is high and most agents are not idle, the contact center may have a need to direct calls to agents whose close ratios are high regardless of cross sales. During the gold-jewelry hour, when call volume is lower, the contact center may have a need to direct calls to agents who can sell gold jewelry with a reasonable close ratio and can effectively cross sell diamonds because more time can be spent on the call encouraging additional sales.
In sum, the conventional methods for selecting one agent over another to service a call at a contact center exhibit shortcomings related to responsiveness to dynamic conditions, to shifting management directives, to changing staff capabilities such as agent performance and proficiency, to multivariate performance metrics, to variations in the state of the contact center, and to indirect and intertwined relationships between factors in the selection process. Accordingly, a need exists for a method and system that can select a preferred agent to service a call and can factor into the selection methodology dynamic situational and environmental influences and shifting agent proficiency and performance.